利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

69 条记录 (耗时 0.025 秒)

    Handwriting symbol recognition accuracy using speech input
    1.
    发明授权
    Handwriting symbol recognition accuracy using speech input 失效
    使用语音输入的手写符号识别精度

    公开(公告)号：US08077975B2

    公开(公告)日：2011-12-13

    申请号：US12037095

    申请日：2008-02-26

    申请人： Lei Ma ,  Yu Shi ,  Frank Kao-ping Soong

    发明人： Lei Ma ,  Yu Shi ,  Frank Kao-ping Soong

    IPC分类号： G06K9/00 ,  G06K9/62 ,  G06K9/72 ,  G06F3/00 ,  G10L15/26 ,  G09G5/00

    CPC分类号： G10L15/24 ,  G06K9/00409 ,  G06K9/00422

    摘要： Described is a bimodal data input technology by which handwriting recognition results are combined with speech recognition results to improve overall recognition accuracy. Handwriting data and speech data corresponding to mathematical symbols are received and processed (including being recognized) into respective graphs. A fusion mechanism uses the speech graph to enhance the handwriting graph, e.g., to better distinguish between similar handwritten symbols that are often misrecognized. The graphs include nodes representing symbols, and arcs between the nodes representing probability scores. When arcs in the first and second graphs are determined to match one another, such as aligned in time and associated with corresponding symbols, the probability score in the second graph for that arc is used to adjust the matching probability score in the first graph. Normalization and smoothing may be performed to correspond the graphs to one another and to control the influence of one graph on the other.

    摘要翻译： 描述了一种双模数据输入技术，通过该技术，手写识别结果与语音识别结果相结合，以提高整体识别精度。 对应于数学符号的手写数据和语音数据被接收并处理（包括被识别）到各个图中。 融合机制使用语音图来增强手写图，例如更好地区分经常被误识别的类似的手写符号。 这些图包括表示符号的节点和表示概率分数的节点之间的弧。 当第一和第二图中的弧被确定为彼此匹配时，例如在时间上对齐并与对应符号相关联时，该弧的第二图中的概率分数用于调整第一图中的匹配概率得分。 可以执行归一化和平滑以将图彼此对应并且控制一个图的影响。

    HANDWRITING SYMBOL RECOGNITION ACCURACY USING SPEECH INPUT
    2.
    发明申请
    HANDWRITING SYMBOL RECOGNITION ACCURACY USING SPEECH INPUT 失效
    使用语音输入的手写符号识别精度

    公开(公告)号：US20090214117A1

    公开(公告)日：2009-08-27

    申请号：US12037095

    申请日：2008-02-26

    申请人： Lei Ma ,  Yu Shi ,  Frank Kao-ping Soong

    发明人： Lei Ma ,  Yu Shi ,  Frank Kao-ping Soong

    IPC分类号： G10L15/00

    CPC分类号： G10L15/24 ,  G06K9/00409 ,  G06K9/00422

    摘要： Described is a bimodal data input technology by which handwriting recognition results are combined with speech recognition results to improve overall recognition accuracy. Handwriting data and speech data corresponding to mathematical symbols are received and processed (including being recognized) into respective graphs. A fusion mechanism uses the speech graph to enhance the handwriting graph, e.g., to better distinguish between similar handwritten symbols that are often misrecognized. The graphs include nodes representing symbols, and arcs between the nodes representing probability scores. When arcs in the first and second graphs are determined to match one another, such as aligned in time and associated with corresponding symbols, the probability score in the second graph for that arc is used to adjust the matching probability score in the first graph. Normalization and smoothing may be performed to correspond the graphs to one another and to control the influence of one graph on the other.

    摘要翻译： 描述了一种双模数据输入技术，通过该技术，手写识别结果与语音识别结果相结合，以提高整体识别精度。 对应于数学符号的手写数据和语音数据被接收并处理（包括被识别）到各个图中。 融合机制使用语音图来增强手写图，例如更好地区分经常被误识别的类似的手写符号。 这些图包括表示符号的节点和表示概率分数的节点之间的弧。 当第一和第二图中的弧被确定为彼此匹配时，例如在时间上对准并与对应符号相关联时，该弧的第二图中的概率分数用于调整第一图中的匹配概率分数。 可以执行归一化和平滑以将图彼此对应并且控制一个图的影响。

    SYMBOL GRAPH GENERATION IN HANDWRITTEN MATHEMATICAL EXPRESSION RECOGNITION
    4.
    发明申请
    SYMBOL GRAPH GENERATION IN HANDWRITTEN MATHEMATICAL EXPRESSION RECOGNITION 有权
    手工数学表达识别中的符号图生成

    公开(公告)号：US20080240570A1

    公开(公告)日：2008-10-02

    申请号：US11693299

    申请日：2007-03-29

    申请人： Yu Shi ,  Frank Kao-Ping Soong ,  Jian-lai Zhou ,  Dongmei Zhang

    发明人： Yu Shi ,  Frank Kao-Ping Soong ,  Jian-lai Zhou ,  Dongmei Zhang

    IPC分类号： G06K9/00

    CPC分类号： G06K9/6296 ,  G06K2209/01

    摘要： A forward pass through a sequence of strokes representing a handwritten equation is performed from the first stroke to the last stroke in the sequence. At each stroke, a path score is determined for a plurality of symbol-relation pairs that each represents a symbol and its spatial relation to a predecessor symbol. A symbol graph having nodes and links is constructed by backtracking through the strokes from the last stroke to the first stroke and assigning scores to the links based on the path scores for the symbol-relation pairs. The symbol graph is used to recognize a mathematical expression based in part on the scores for the links and the mathematical expression is stored.

    摘要翻译： 从序列中的第一行程到最后一个行程执行表示手写方程的笔画序列的向前传递。 在每个笔划处，确定多个符号 - 关系对的路径分数，每个符号 - 关系对都表示符号及其与前身符号的空间关系。 具有节点和链接的符号图是通过从最后笔划到第一笔划的笔画回溯构成的，并且基于符号 - 关系对的路径得分将分数分配给链接。 符号图用于部分地基于链接的分数来识别数学表达式，并存储数学表达式。

    Segmentation posterior based boundary point determination
    5.
    发明申请
    Segmentation posterior based boundary point determination 审中-公开
    分段后验边界点确定

    公开(公告)号：US20080189109A1

    公开(公告)日：2008-08-07

    申请号：US11702373

    申请日：2007-02-05

    申请人： Yu Shi ,  Frank Kao-Ping Soong

    发明人： Yu Shi ,  Frank Kao-Ping Soong

    IPC分类号： G10L15/00

    CPC分类号： G10L15/04

    摘要： Boundary points for speech in an audio signal are determined based on posterior probabilities for the boundary points given a set of possible segmentations of the audio signal. The boundary point posterior probability is determined based on a set of level posterior probabilities that each provide the probability of a sequence of feature vectors given one of the segmentations in the set of possible segmentations.

    摘要翻译： 基于给定一组可能的音频信号分段的边界点的后验概率来确定音频信号中的语音的边界点。 基于一组级别后验概率来确定边界点后验概率，每组提供一组特征向量的概率，该特征向量在可能的分段集合中给出一个分段。

    Auto segmentation based partitioning and clustering approach to robust endpointing
    6.
    发明申请
    Auto segmentation based partitioning and clustering approach to robust endpointing 失效
    基于自动分割的分区和聚类方法进行鲁棒终点

    公开(公告)号：US20080059169A1

    公开(公告)日：2008-03-06

    申请号：US11504280

    申请日：2006-08-15

    申请人： Yu Shi ,  Frank Kao-ping Soong ,  Jian-lai Zhou

    发明人： Yu Shi ,  Frank Kao-ping Soong ,  Jian-lai Zhou

    IPC分类号： G10L15/20

    CPC分类号： G10L25/87

    摘要： Possible segmentations for an audio signal are scored based on distortions for feature vectors of the audio signal and the total number of segments in the segmentation. The scores are used to select a segmentation and the selected segmentation is used to identify a starting point and an ending point for a speech signal in the audio signal.

    摘要翻译： 基于音频信号的特征向量的失真和分段中的段的总数，对音频信号进行可能的分割。 分数用于选择分割，并且所选择的分割用于识别音频信号中的语音信号的起始点和终点。

    Online Handwriting Expression Recognition
    8.
    发明申请
    Online Handwriting Expression Recognition 审中-公开
    在线手写表达识别

    公开(公告)号：US20090245646A1

    公开(公告)日：2009-10-01

    申请号：US12058506

    申请日：2008-03-28

    申请人： Yu Shi ,  Frank Kao-Ping Soong

    发明人： Yu Shi ,  Frank Kao-Ping Soong

    IPC分类号： G06K9/78

    CPC分类号： G06K9/00422 ,  G06K9/00879

    摘要： One way of recognizing online handwritten mathematical expressions is to use a one-pass dynamic programming based symbol decoding generation algorithm. This method embeds segmentation into symbol identification to form a unified framework for symbol recognition. Along with decoding, a symbol graph is produced. Besides accurately recognizing handwritten mathematical expressions, this method can produce high quality symbol graphs. This method uses six knowledge source models to help search for possible symbol hypotheses during the decoding process. Here, knowledge source exponential weights and a symbol insertion penalty are used to weigh the various knowledge source model probabilities to increase accuracy.

    摘要翻译： 识别在线手写数学表达式的一种方法是使用基于单程动态规划的符号解码生成算法。 该方法将分段嵌入符号识别中，形成符号识别的统一框架。 随着解码，产生符号图。 除了精确地识别手写数学表达，这种方法可以产生高质量的符号图。 该方法使用六种知识源模型来帮助在解码过程中搜索可能的符号假设。 这里，知识源指数权重和符号插入罚分用于权衡各种知识源模型概率以提高准确性。